Comparative Analysis of Prediction Algorithms for Heart Diseases

Title

Comparative Analysis of Prediction Algorithms for Heart Diseases

Creator

Karun I.

Description

Cardiovascular diseases (CVDs) are the leading source of demises universally: More individuals perish yearly from heart disease than due to any other reason. An estimated 17.9 million humans died from CVDs in 2016, constituting 31% of all global deaths. [1] Such high rates of death due to heart diseases have to cease. This idea can be accelerated by the prediction of risk of CVDs. If a person can be medicated much earlier, before they have any symptoms that can be far more beneficial in averting sickness. The paper strives to communicate this issue of heart diseases employing various prediction models and optimizing them for better outcomes. The accuracy of each algorithm guides to a relative enquiry of these prediction models, forming a solid base for further research, finer prognosis and detection of diabetes. 2021, Springer Nature Singapore Pte Ltd.

Source

Advances in Intelligent Systems and Computing, Vol-1158, pp. 583-591.

Date

2021-01-01

Publisher

Springer Science and Business Media Deutschland GmbH

Subject

Classification; Comparative analysis; Disease prediction; Heart disease prediction; Machine learning; Predictive modeling; Receiver operating characteristics curve

Coverage

Karun I., Department of Mathematics, Christ (Deemed to be University), Bengaluru, India

Rights

Restricted Access

Relation

ISSN: 21945357; ISBN: 978-981154408-8

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1007/978-981-15-4409-5_53

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85096493708&doi=10.1007%2f978-981-15-4409-5_53&partnerID=40&md5=7c983ba01a3891a692432b35d647c80e